Machine Learning for Evolution Strategies

Oliver Kramer

ISBN 10: 331933381X / ISBN 13: 9783319333816

Published by Springer International Publishing, 2016

About this Item

Machine Learning for Evolution Strategies | Oliver Kramer | Buch | ix | Englisch | 2016 | Springer International Publishing | EAN 9783319333816 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 103890319

Bibliographic Details

• Title: Machine Learning for Evolution Strategies
• Publisher: Springer International Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 331933381X
• ISBN 13: 9783319333816
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 14D millimeters 241 millimeters width by 160 millimeters height by 14 millimeters depth
• Weight: 377 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book introduces numerous algorithmic hybridizations between both worlds that show how machine learning can improve and support evolution strategies. The set of methods comprises covariance matrix estimation, meta-modeling of fitness and constraint functions, dimensionality reduction for search and visualization of high-dimensional optimization processes, and clustering-based niching. After giving an introduction to evolution strategies and machine learning, the book builds the bridge between both worlds with an algorithmic and experimental perspective. Experiments mostly employ a (1+1)-ES and are implemented in Python using the machine learning library scikit-learn. The examples are conducted on typical benchmark problems illustrating algorithmic concepts and their experimental behavior. The book closes with a discussion of related lines of research.